Comparison of a genetic programming approach with ANFIS for power amplifier behavioral modeling and FPGA implementation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Galaviz-Aguilar:2019:SC,
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author = "Jose Alejandro Galaviz-Aguilar and Patrick Roblin and
Jose Ricardo Cardenas-Valdez and Emigdio Z.-Flores and
Leonardo Trujillo and Jose-Cruz Nunez Perez and
Oliver Schuetze",
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title = "Comparison of a genetic programming approach with
{ANFIS} for power amplifier behavioral modeling and
{FPGA} implementation",
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journal = "Soft Computing",
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year = "2019",
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volume = "23",
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number = "7",
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pages = "2463--2481",
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keywords = "genetic algorithms, genetic programming, anfis digital
predistortion linearisation power amplifier modelling
radio frequency",
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ISSN = "1432-7643",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/soco/soco23.html#Galaviz-Aguilar19",
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DOI = "doi:10.1007/s00500-017-2941-8",
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abstract = "Accurate modelling of power amplifiers (PA) is of up
most importance in the design process of wireless
communication systems where a high linearity and
efficiency is required. To deal with the nonlinear
behaviour of PAs effectively a linearisation stage is
applied to minimise the distortions of in-band and
adjacent transmission channels, which translate to an
improvement of the signal integrity and the operation
cost of the transmitter system. This paper presents a
method based on genetic programming with a local search
heuristic (GP-LS) to emulate the electrical memory
effects by using the characteristic conversion curves
of the radio frequency (RF) PA NXP Semiconductor of 10
W GaN HEMT working at 2.34 GHz. This method is compared
with an Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
through several performance metrics (NMSE, MAE and
correlation coefficient), with GP-LS achieving a better
modelling accuracy. Moreover, the models produced by
GP-LS permit a reduction in the required hardware
resources, when it is implemented on a
Field-Programmable Gate Array through the DSP Builder
tool. The models are derived using a data-driven
approach, posed in two different ways. Firstly,
experiments are performed using a testbed Arria V GX
for a flexible vector signal generation that provides
the raw data of the PA characterisation using an
LTE-Advanced signal with 10-MHz bandwidth. Secondly,
the modelling is derived from a filtered version of the
data and then adding a high-frequency signal as a post
processing step to approximate the true behaviour of
the system. In both cases, the models are generated
with ANFIS and GP-LS, performing extensive logic-based
simulations and implementing the models on a Cyclone
III development board. Both approaches are compared
based on accuracy and required hardware resources, with
GP-LS substantially outperforming ANFIS. These results
suggest that the GP-LS models can be implemented in a
digital pre-distortion chain and used in the
linearization stage for a RF-PA.",
-
notes = "journals/soco/Galaviz-Aguilar19",
- }
Genetic Programming entries for
Jose Alejandro Galaviz-Aguilar
Patrick Roblin
Jose Ricardo Cardenas Valdez
Emigdio Z-Flores
Leonardo Trujillo
Jose Cruz Nunez Perez
Oliver Schuetze
Citations